• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.1
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• pp.5-14
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• 2017

Many web services which use OAuth Protocol offer users to log in using their personal profile information given by resource servers. This method reduces the inconvenience of the users to register for new membership. However, at the time a user finishes using OAuth client web service, even if he logs out of the client web service, the resource server remained in the login state may cause the problem of leaking personal information. In this paper, we propose a solution to mitigate the threat by providing an additional security behavior check: when a user requests to log out of the Web Client service, he or she can make decision whether or not to log out of the resource server via confirmation notification regarding the state of the resource server. By utilizing the proposed method, users who log in through the OAuth Protocol in the public PC environment like department stores, libraries, printing companies, etc. can prevent the leakage of personal information issues that may arise from forgetting to check the other OAuth related services. To verify our study, we implement a Client Web Service that uses OAuth 2.0 protocol and integrate it with our security behavior check. The result shows that with this additional function, users will have a better security when dealing with resource authorization in OAuth 2.0 implementation.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.209-228
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• 2011

Web search behavior has evolved. People now search using many diverse information devices in various situations. To monitor these scattered and shifting search patterns, an improved way of learning and analysis are needed. Traditional web search studies relied on the server transaction logs and single query instance analysis. Since people use multiple smart devices and their searching occurs intermittently through a day, a bundled query research could look at the whole context as well as penetrating search needs. To observe and analyze bundled queries, we developed a proprietary research software set including a log catcher, query bundling tool, and bundle monitoring tool. In this system, users' daily search logs are sent to our analytic server, every night the users need to log on our bundling tool to package his/her queries, a built in web survey collects additional data, and our researcher performs deep interviews on a weekly basis. Out of 90 participants in the study, it was found that a normal user generates on average 4.75 query bundles a day, and each bundle contains 2.75 queries. Query bundles were categorized by; Query refinement vs. Topic refinement and 9 different sub-categories.

• 한국디지털정책학회:학술대회논문집
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• 2004.11a
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• pp.211-219
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• 2004

Due to rapid increases in Internet users, it becomes essential to provide well-established web services and monitor web server's load for the sake of reliable web server management. The existing web server load monitoring has been based on such cable methods as RPC, RMI, CORBA and etc. But it has the limitation in bringing information both anywhere and anytime over the Internet. This thesis is aimed to realize real-time wireless web server monitoring system based on Wireless Application Protocol (WAP). As any user can log on wirelessly to the Internet at any time through wireless terminals like PDA, the realization will make possible instant and real-time web server monitoring.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.143-146
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• 2004

With the rapid growth of e-commerce, marketers are able to observe not only purchasing behavior on what and when customers purchased, but also the individual Web usage behavior that affect purchasing. The richness of this information has the potential to provide marketers with an in-depth understanding of customer. Using commonly available Web log data, this paper examines Web usage behaviors at the individual level. By decomposing the buying process into a pattern of visits and purchase conversion at each visit, we can better understand the relationship between Web usage behavior and purchase decision. This allows us to more accurately forecast a shopper's future purchase decision at the site and hence determine the value of individual customers to the siteAccording to our research, not only information seeking behavior but also visiting duration of a customer and participative behavior such as participation in event should be considered as important predicators of purchase decision of customer in a cosmetic internet shopping mall.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.337-340
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• 2022

SQL Injection attacks are one of the older attack techniques and are the dominant type of hacking attempts against web services. There have been many attempts to hack SQL injection attacks by exposing data or obtaining privileges. In this paper, we implement a log analysis system that can respond to SQL injection attacks in real time using the open source ELK Stack. did. By providing a visualization of SQL injection attack log data through the implemented system, it is expected that users will be able to easily grasp the degree of attack risk and quickly prepare for attacks.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.9
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• pp.530-538
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• 2002

In this paper, we propose a new caching strategy for web servers. The proposed algorithm collects on]y the statistics of the requested file, for example the popularity, when a request arrives. And, at times, only files with higher popularity are cached all together. Because the cache remains unchanged until the cache is made newly, web server can use very efficient data structure for cache to determine whether a file is in the cache or not. This increases greatly tile efficiency of cache manipulation. Furthermore, the experiment that is performed with real log files built by web servers shows that the cache hit ratio and the cache hit ratio are better than those produced by LRU. The proposed algorithm has a drawback such that the cache hit ratio may decrease when the popularity of files that is not in the cache explodes instantaneously. But in our opinion, such explosion happens infrequently, and it is easy to implement the web servers to adapt them to such unusual cases.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.192-197
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• 2001

A recommendation system tracks past actions of a group of users to make a recommendation to individual members of the group. The computer-mediated marketing and commerce have grown rapidly nowadays so the concerns about various recommendation procedures are increasing. We introduce a recommendation methodology by which e-commerce sites suggest new products of services to their customers. The suggested methodology is based on web log analysis, product taxonomy, and association rule mining. A product recommendation system is developed based on our suggested methodology and applied to a Korean internet shopping mall. The validity of our recommendation system is discussed with the analysis of a real internet shopping mall case.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.190-192
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• 2002

데이터 마이닝(Data Mining)이란 저장된 많은 양의 자료로부터 통계적 수학적 분석방법을 이용하여 다양한 가치 있는 정보를 찾아내는 일련의 과정이다. 데이터 클러스터링은 이러한 데이터 마이닝을 위한 하나의 중요한 기법이다. 본 논문에서는 Fuzzy C-Means 알고리즘을 이용하여 웹 사용자들의 행위가 기록되어 있는 웹 로그 데이터를 데이터 클러스터링 하는 방법에 관하여 연구하고자 한다. Fuzzv C-Means 클러스터링 알고리즘은 각 데이터와 각 클러스터 중심과의 거리를 고려한 유사도 측정에 기초한 목적 함수의 최적화 방식을 사용한다. 웹 로그 데이터의 여러 필드 중에서 사용자 IP, 시간, 웹 페이지 필드를 WLDF(Web Log Data for FCM)으로 가공한 후, 다차원 Fuzzy C-Means 클러스터링을 한다. 그리고 이를 이용하여 샘플 데이터와 임의의 데이터간의 유사 패턴 분석을 하고자 한다.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.335-339
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• 2003

We proposed a Web cache replacement technique of a divided scope base that considered a size reference characteristics of a Web object for efficient operation of a Web base system and, in this study, analyzed performance of the replacement technique that proposed it though an experiment. We analyzed a reference characteristics of size to occur by a user reference characteristics through log analysis of a Web Base system in an experiment. And we divide storage scope of a cache server as its analysis result and tested this replacement technique based n divided scope. The proposed technique has a flexibility about a change of a reference characteristics of a user. Also, experiment result, we compared it with LRU and the LRUMIN which were an existing replacement technique and confirmed an elevation of an object hit ratio.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.443-446
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• 2002

In this research, we suggest a Web-based hybrid recommendation mechanism using CBR (Case-Based Reasoning) and web data mining. Data mining is used as an efficient mechanism in reasoning for relationship between goods, customers' preference and future behavior. CBR systems are normally used in problems for which it is difficult to define rules. We use CBR as an AI tool to recommend the similar purchase case. A Web-log data gathered in real-world Internet shopping mall was given to illustrate the quality of the proposed mechanism. The results showed that the CBR and web data mining-based hybrid recommendation mechanism could reflect both association knowledge and purchase information about our former customers.